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QiaoyuZheng
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RP3D-DiagDS

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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ValueError
Message:      Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/QiaoyuZheng/RP3D-DiagDS@dc6ecae276d1f3bb8a9d465a935585f8a79c3db2/RP3D_train.json.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 231, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
                  for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 172, in _generate_tables
                  raise ValueError(
              ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/QiaoyuZheng/RP3D-DiagDS@dc6ecae276d1f3bb8a9d465a935585f8a79c3db2/RP3D_train.json.

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RP3D-DiagDS

Overview of RP3D-DiagDS. There are 39,026 cases (192,675 scans) across 7 human anatomy regions and 9 diverse modalities covering 930 ICD-10-CM codes.

results

About Dataset

There are totally 4 json files:

  1. RP3D_train.json: Data used for model training. This file is organized at case level (there may be more than one kind of modality and anatomy in a case. For more details, refer to the paper Large-scale Long-tailed Disease Diagnosis on Radiology.
  2. RP3D_test_json: Data used for model evaluation.
  3. disorder_label_dict.json: For disorder granularity. There are totally 5569 ( 5568 abnormal and 1 noraml) label. There disorders are sorted in descending order based on the corresponding case number for evaluation.
  4. icd10_label_dict.json: For ICD-10-CM granularity. There are totally 931 ( 930 abnormal and 1 noraml) label. There disorders are sorted in descending order based on the corresponding case number for evaluation.

Attention! In RP3D_{train/test}.json file. A 'url' key corresponds to a 'Case', and there maybe multiple 'samples' in a 'Case' under the 'Samples' key.

About Model Checkpoint

Please refer to RP3D-DiagModel

For more information about the code please refer to our instructions on github to download and use.

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